Large-scale, multi-user, multiple-input multiple-output (MIMO) architectures typically increase the hardware and software complexity of wireless systems by increasing the number of radio frequency (RF) chains to increase both multiplexing and beamforming gains. This results in poor throughput efficiency, due to the increased energy consumption and wireless channel hardening; high coordination overhead due to maintaining fine-grained coordination of a large number of antennas; and no support from existing high-speed wireless standards and hardware.
Existing attempts to combine analog beamforming with digital RF chains include integrating phase-array antennas with non-MIMO base stations (BSes). However, these approaches choose an optimal beam pattern using an exhaustive search of all codebook entries, which scales with the size of the phased-array antenna. Faster beam searches, such as those based on simulated annealing, can reduce the search time, but the overhead still increases with the size of the phased array.
Joint optimization schemes have also been proposed for beamforming. However, these use tight integration between the analog phased array and the digital RF chains. This level is not feasible for a solution that is to be backwards compatible with existing BSes.
Two-level beamforming is also employed in such areas as MIMO radar. However, such systems are purpose-built for object tracking, not communications, and also have tight coordination between analog and digital RF components. The distributed coordination scheme increases throughput through opportunistic use of degrees of freedom, but this needs precise clock phase and frequency synchronization. Other centralized, coordinated, multipoint systems demonstrate gains from cooperative transmissions across access points, but these gains come at the cost of significant synchronization and inter-cell channel state information (CSI) sharing overhead. Such overhead is not practical for large-scale deployment in real-world cellular networks.